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Autres articles (32)
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Contribute to a better visual interface
13 avril 2011MediaSPIP is based on a system of themes and templates. Templates define the placement of information on the page, and can be adapted to a wide range of uses. Themes define the overall graphic appearance of the site.
Anyone can submit a new graphic theme or template and make it available to the MediaSPIP community. -
Contribute to translation
13 avril 2011You can help us to improve the language used in the software interface to make MediaSPIP more accessible and user-friendly. You can also translate the interface into any language that allows it to spread to new linguistic communities.
To do this, we use the translation interface of SPIP where the all the language modules of MediaSPIP are available. Just subscribe to the mailing list and request further informantion on translation.
MediaSPIP is currently available in French and English (...) -
Emballe médias : à quoi cela sert ?
4 février 2011, parCe plugin vise à gérer des sites de mise en ligne de documents de tous types.
Il crée des "médias", à savoir : un "média" est un article au sens SPIP créé automatiquement lors du téléversement d’un document qu’il soit audio, vidéo, image ou textuel ; un seul document ne peut être lié à un article dit "média" ;
Sur d’autres sites (7082)
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Revert "lavu/atomic : add support for the new memory model aware gcc built-ins"
7 mars 2017, par James AlmerRevert "lavu/atomic : add support for the new memory model aware gcc built-ins"
This reverts commit faa9d2982969c999ab0e443a226eff116f7f8e4b.
This change became superfluous when support for C11 atomics was introduced.
Reverting it will make the removal of this implementation in an upcoming
merge conflict free.Reviewed-by : wm4 <nfxjfg@googlemail.com>
Signed-off-by : James Almer <jamrial@gmail.com> -
Celery to process task and modify the model fields
15 juillet 2015, par RobinI would like to convert video into mp4 using
ffmpeg
andcelery
for the asynchronous task. When user uploads a video, it will be for theoriginal_video
and save it. After that I want celery to convert it into a different version for themp4_720
field. However I am confused on how to apply that logic using celery.app.models.py :
class Video(models.Model):
title = models.CharField(max_length=75)
pubdate = models.DateTimeField(default=timezone.now)
original_video = models.FileField(upload_to=get_upload_file_name)
mp4_720 = models.FileField(upload_to=get_upload_file_name, blank=True, null=True)
converted = models.BooleanField(default=False)app.views.py :
def upload_video(request):
if request.POST:
form = VideoForm(request.POST, request.FILES)
if form.is_valid():
video = form.save(commit=False)
video.save()
// Celery to convert the video
convert_video.delay(video)
return HttpResponseRedirect('/')
else:
form = VideoForm()
return render(request, 'upload_video.html', {
'form':form
})app.tasks.py :
@app.task
def convert_video(video):
// Convert the original video into required format and save it in the mp4_720 field using the following command:
//subprocess.call('ffmpeg -i (path of the original_video) (video for mp4_720)')
// Change the converted boolean field to True
// SaveBasically my question is how to save the converted video in mp4_720. Your help and guidance will be very much appreciated. Thank you.
** update **
What I want that method to do is first convert the video.original_video and then save the converted video in the video.mp4_720 field. If all has been done correctly, change the video.converted to True. How do I define the method to do so ?
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Revision ac50b75e50 : Use balanced model for intra prediction mode coding This commit replaces the pr
20 juin 2015, par Jingning HanChanged Paths :
Modify /vp9/common/vp9_entropymode.c
Modify /vp9/common/vp9_entropymode.h
Modify /vp9/decoder/vp9_decodeframe.c
Modify /vp9/decoder/vp9_decodemv.c
Modify /vp9/encoder/vp9_bitstream.c
Modify /vp9/encoder/vp9_encodeframe.c
Modify /vp9/encoder/vp9_pickmode.c
Modify /vp9/encoder/vp9_rd.c
Modify /vp9/encoder/vp9_rdopt.c
Use balanced model for intra prediction mode codingThis commit replaces the previous table based intra mode model
coding with a more balanced entropy coding system. It reduces the
decoder lookup table size by 1K bytes. The key frame compression
performance is about even on average. There are a few points where
the compression performance is improved by over 5%. Most test
points are fairly close to the lookup table approach.Change-Id : I47154276c0a6a22ae87de8845bc2d494681b95f6